Evaluating the Computational Values of Suspended Particles Below 10 μm With Their Actual Concentration

Abstract

Background & Aims of the Study: Dust as a phenomenon is among the significant problems in numerous regions of Iran and other countries. Empirical equations can be used to estimate the concentration of particulate matter. This study evaluated computational values of suspended particles less than 10 μm with their actual concentration in Ahvaz city based on a linear regression model. Materials and Methods: This descriptive cross-sectional study was conducted from April 2016 to March 2018. The dust images were obtained from the MODIS sensor of the Aqua satellite. The meteorological data included 3-hour horizontal visibility data recorded in m. PM10 concentration data were obtained from the Environment Organization. Accordingly, 5 empirical equations between horizontal visibility and PM10 have been used in this case. The calculated values of particulate matter less than 10 μm in Ahvaz City, Iran, were evaluated with actual values of PM10 based on the linear regression model. Results: The study results suggested that the computational R index for empirical equations had higher accuracy in 2017 data. The coefficients of determination using D’Almeida (1986), Dayan (1986), Chung (2003), Jugder et al. (2014), and Camino et al. (2015) indicators were calculated as 0.87, 0.806, 0.745, 0.873, and 0.866, respectively. Conclusion: Jugder et al. (2014) index with R² equal to 0.548667 was the best index for estimating PM10 in this region. The study results showed that empirical equations could estimate particulate matter and dust in southwestern Iran.